Data Compression W5

Question 1

What is the goal of data compression?

Answer 1

To reduce redundancy in data and save space.

Question 2

What is the difference between message, data, and information?

Answer 2

Message: What you’re trying to say.

Data: Symbols used to express it.

Information: The amount of surprise (newness).

Question 3

What is redundancy in data?

Answer 3

Repeating or predictable information that can be removed to save space.

Question 4

What is information theory and who founded it?

Answer 4

The study of quantifying and compressing information; founded by Claude Shannon in 1948.

Question 5

What’s an example of lossless compression?

Answer 5

Assigning shorter binary codes to common patterns (e.g., Huffman coding).

Question 6

When does compression work best?

Answer 6

When data has high redundancy (e.g., predictable patterns or repeated values).

Question 7

What is the average bits per customer in the vegetarian example?

Answer 7

0.78 bits per customer (achieving lossless compression).

Question 8

What’s the key idea behind compression?

Answer 8

Store only the unpredictable (surprising) parts of data.